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Food Science & Technology

Evaluating the impact of improved technology adoption in traditional poultry farming on potential outcomes of farmers: evidence from rural Togo

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Article: 2341091 | Received 11 Dec 2023, Accepted 04 Apr 2024, Published online: 16 May 2024

References

  • Alem, Y., & Ruhinduka, R. D. (2020). Saving Africa’s tropical forests through energy transition: A randomized control trial in Tanzania. Economic Record, 58, 1. https://doi.org/10.1111/j.1475-4932.1982.tb00356.x
  • Angrist, J. D., Imbens, G. W., & Rubin, D. B. (1996). Identification of causal effects using instrumental variables. Journal of the American Statistical Association, 91(434), 444–15. https://doi.org/10.1080/01621459.1996.10476902
  • Ao, G., Liu, Q., Qin, L., Chen, M., Liu, S., & Wu, W. (2021). Organization model, vertical integration, and farmers’ income growth: Empirical evidence from large-scale farmers in Lin’an, China. PLoS One, 16(6), e0252482. https://doi.org/10.1371/journal.pone.0252482
  • Asfaw, S., Kassie, M., Simtowe, F., & Lipper, L. (2012). Poverty reduction effects of agricultural technology adoption: A micro-evidence from rural Tanzania. Journal of Development Studies, 48(9), 1288–1305. https://doi.org/10.1080/00220388.2012.671475
  • Awotide, B. A., Alene, A. D., Abdoulaye, T., & Manyong, V. M. (2015). Impact of agricultural technology adoption on asset ownership: The case of improved cassava varieties in Nigeria. Food Security, 7(6), 1239–1258. https://doi.org/10.1007/s12571-015-0500-7
  • Bachewe, F. N., Berhane, G., Minten, B., & Taffesse, A. S. (2018). Agricultural transformation in Africa? Assessing the evidence in Ethiopia. World Development, 105, 286–298. https://doi.org/10.1016/j.worlddev.2017.05.041
  • Balakrishnan, R., Linsmeier, T. J., & Venkatachalam, M. (1996). Financial benefits from JIT adoption: Effects of customer concentration and cost structure. Accounting Review, 71(2), 183–205.
  • Belay, M., & Mengiste, M. (2021). The ex-post impact of agricultural technology adoption on poverty: Evidence from north Shewa zone of Amhara region, Ethiopia. International Journal of Finance & Economics, 28(2), 1327–1337. https://doi.org/10.1002/ijfe.2479
  • Benin, S., & Yu, B. (2012). Complying with the Maputo declaration target: Trends in public agricultural expenditures and implications for pursuit of optimal allocation of public agricultural spending. ReSAKSS annual trends and outlook report. International Food Policy Research Institute (IFPRI).
  • Besedeš, T., & Prusa, T. J. (2011). The role of extensive and intensive margins and export growth. Journal of Development Economics, 96(2), 371–379. https://doi.org/10.1016/j.jdeveco.2010.08.013
  • Bhattacharyya, S., Rai, C. K., Patnaik, N. M., Verma, R. K., & Roy, P. (2023). Adoption of sustainable dryland technologies for improving livelihood of farmers in developing countries. In A. Naorem & D. Machiwal (Eds.), Enhancing resilience of dryland agriculture under changing climate (pp. 597–624). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-9159-2_30
  • Black, J. D. (1929). The extensive vs. the intensive margin. Journal of Farm Economics, 11(2), 331. https://doi.org/10.2307/1230441
  • Carter, M. R., Tjernström, E., & Toledo, P. (2019). Heterogeneous impact dynamics of a rural business development program in Nicaragua. Journal of Development Economics, 138, 77–98. https://doi.org/10.1016/j.jdeveco.2018.11.006
  • Chaney, T. (2008). Distorted gravity: The intensive and extensive margins of international trade. American Economic Review, 98(4), 1707–1721. https://doi.org/10.1257/aer.98.4.1707
  • Chen, P. J., O’Sullivan, S., & Pyke, S. (2024). Hybrid governance and welfare standards for broiler chickens raised for human consumption. Australian Journal of Public Administration, 1–24. https://doi.org/10.1111/1467-8500.12625
  • Cole, S. A., & Fernando, A. N. (2021). ‘Mobile’izing agricultural advice technology adoption diffusion and sustainability. The Economic Journal, 131(633), 192–219. https://doi.org/10.1093/ej/ueaa084
  • De Janvry, A. (1973). A socioeconomic model of induced innovations for Argentine agricultural development. The Quarterly Journal of Economics, 87(3), 410–435. https://doi.org/10.2307/1882013
  • Dias Avila, A. F., & Evenson, R. E. (2010). Chapter 72: Total factor productivity growth in agriculture. The role of technological capital. In Kenneth J. Arrow & Michael D. Intriligator (Eds.), Handbook of agricultural economics (1st ed., Vol. 4). Elsevier. https://doi.org/10.1016/S1574-0072(09)04072-9
  • El Ghak, T., Gdairia, A., & Abassi, B. (2020). High-tech entrepreneurship and total factor productivity: The case of innovation-driven economies. Journal of the Knowledge Economy, 12(3), 1152–1186. https://doi.org/10.1007/s13132-020-00659-9
  • Evenson, R. E., & Fuglie, K. O. (2010). Technology capital: The price of admission to the growth club. Journal of Productivity Analysis, 33(3), 173–190. https://doi.org/10.1007/s11123-009-0149-3
  • Feder, G., Just, R. E., & Zilberman, D. (1985). Adoption of agricultural innovations in developing countries: A survey. Economic Development and Cultural Change, 33(2), 255–298. https://doi.org/10.1086/451461
  • Feder, G., & Umali, D. L. (1993). The adoption of agricultural innovations: A review. Technological Forecasting and Social Change, 43(3–4), 215–239. https://doi.org/10.1016/0040-1625(93)90053-A
  • Fellegi, I. P. (2003). Méthode et pratiques d’enquêtes. N° 12-587-X au catalogue (Survey methods and practices). Statistics Canada.
  • Food and Agriculture Organization of the United Nations. (2014). Food and Agriculture Organization of the United Nations in collaboration with the International Fund for Agricultural Development and Kyeema Foundation. N°16. Decision tools for family poultry development. FAO animal production and health guidelines (Vol. 16). Rome, Italy.
  • Food and Agriculture Organization of the United Nations. (2015). Secteur Avicole Togo. Revues nationales de l’élevage de la division de la production et de la santé animales de la FAO (N°9). Poultry sector in Togo. National livestock reviews by the FAO Animal Production and Health Division. N°9. Rome, Italy.
  • Food and Agriculture Organization of the United Nations. (2017). The future of food and agriculture – Trends and challenges. https://www.fao.org/3/i6583e/i6583e.pdf
  • Foster, A. D., & Rosenzweig, M. R. (1995). Learning by doing and learning from others: Human capital and technical change in agriculture. Journal of Political Economy, 103(6), 1176–1209. https://doi.org/10.1086/601447
  • Foster, A. D., & Rosenzweig, M. R. (2010). Microeconomics of technology adoption. Annual Review of Economics, 2(1), 395–424. https://doi.org/10.1146/annurev.economics.102308.124433
  • Fuglie, K., Gautam, M., Goyal, A., & Maloney, W. F. (2020). Harvesting prosperity: Technology and productivity growth in agriculture. World Bank. https://doi.org/10.1596/978-1-4648-1393-1
  • Gallardo, R. K., & Sauer, J. (2018). Adoption of labor-saving technologies in agriculture. Annual Review of Resource Economics, 10(1), 185–206. https://doi.org/10.1146/annurev-resource-100517-023018
  • Gao, Y., Zhao, D., Yu, L., & Yang, H. (2020). Influence of a new agricultural technology extension mode on farmers’ technology adoption behavior in China. Journal of Rural Studies, 76(March), 173–183. https://doi.org/10.1016/j.jrurstud.2020.04.016
  • Gollin, D., Morris, M., & Byerlee, D. (2005). Technology adoption in intensive post-green revolution systems. American Journal of Agricultural Economics, 87(5), 1310–1316. https://doi.org/10.1111/j.1467-8276.2005.00824.x
  • Gong, B. (2020). New growth accounting. American Journal of Agricultural Economics, 102(2), 641–661. https://doi.org/10.1002/ajae.12009
  • Heckman, J. J. (1992). Haavelmo and the birth of modern econometrics: A review of the history of econometric ideas by Mary Morgan. Journal of Economic Literature, 30(2), 876–886.
  • Heckman, J. J. (1997). Instrumental variables: A study of implicit behavioral assumptions used in making program evaluations. The Journal of Human Resources, 32(3), 441–462. https://doi.org/10.2307/146178
  • Heckman, J. J., Ichimura, H., & Todd, P. (1997). Matching as an econometric evaluation estimator. Review of Economic Studies, 65(2), 261–294. https://doi.org/10.1111/1467-937X.00044
  • Heckman, J. J., & Vytlacil, E. (2001). Causal parameters, structural equations, treatment effects and randomized evaluations of social programs [Manuscript]. University of Chicago and American Bar Foundation.
  • Heckman, J. J., & Vytlacil, E. (2005). Structural equations, treatment effects, and econometric policy evaluation. Econometrica, 73(3), 669–738. https://doi.org/10.1111/j.1468-0262.2005.00594.x
  • Imbens, G. W., & Angrist, J. D. (1994). Identification and estimation of local average treatment effects. Econometrica, 62(2), 467–475. https://doi.org/10.2307/2951620
  • Issahaku, G., & Abdulai, A. (2020). Adoption of climate–smart practices and its impact on farm performance and risk exposure among smallholder farmers in Ghana. Australian Journal of Agricultural and Resource Economics, 64(2), 396–420. https://doi.org/10.1111/1467-8489.12357
  • Khandker, S. R., Koolwal, G. B., & Samad, H. A. (2009). Handbook on impact evaluation. Quantitative methods and practices. The Word Bank. https://doi.org/10.1596/978-0-8213-8028-4
  • Khonje, M., Manda, J., Alene, A. D., & Kassie, M. (2015). Analysis of adoption and impacts of improved maize varieties in eastern Zambia. World Development, 66, 695–706. https://doi.org/10.1016/j.worlddev.2014.09.008
  • Kolavalli, S., Birner, R., & Flaherty, K. (2012). The comprehensive Africa agriculture program as a collective institution (IFPRI Discussion Paper 1238). International Food Policy Research Institute (IFPRI).
  • Kuan, K. K. Y., & Chau, P. Y. K. (2001). A perception-based model for EDI adoption in small businesses using a technology–organization–environment framework. Information & Management, 38(8), 507–521. https://doi.org/10.1016/S0378-7206(01)00073-8
  • Kumaresan, A., Bujarbaruah, K. M., Pathak, K. A., Chhetri, B., Ahmed, S. K., & Haunshi, S. (2008). Analysis of a village chicken production system and performance of improved dual purpose chickens under a subtropical hill agro-ecosystem in India. Tropical Animal Health and Production, 40(6), 395–402. https://doi.org/10.1007/s11250-007-9097-y
  • Lee, D. (2005). Agricultural sustainability and technology adoption: Issues and policies for developing countries. American Journal of Agricultural Economics, 87(5), 1325–1334. https://doi.org/10.1111/j.1467-8276.2005.00826.x
  • Magothe, T. M., Okeno, T. O., Muhuyi, W. B., & Kahi, A. K. (2012). Indigenous chicken production in Kenya: I. Current status. World’s Poultry Science Journal, 68(1), 119–132. https://doi.org/10.1017/S0043933912000128
  • Magruder, J. R. (2018). An assessment of experimental evidence on agricultural technology adoption in developing countries. Annual Review of Resource Economics, 10(1), 299–316. https://doi.org/10.1146/annurev-resource-100517-023202
  • Mahanty, S., Doron, A., & Hamilton, R. (2023). A policy and research agenda for Asia’s poultry industry. Asia & the Pacific Policy Studies, 10(1–3), 63–72. https://doi.org/10.1002/app5.377
  • Mamo, N., Bhattacharyya, S., & Moradi, A. (2019). Intensive and extensive margins of mining and development: Evidence from Sub-Saharan Africa. Journal of Development Economics, 139(2), 28–49. https://doi.org/10.1016/j.jdeveco.2019.02.001
  • McClaughlin, E., Elliott, S., Jewitt, S., Smallman-Raynor, M., Dunham, S., Parnell, T., Clark, M., & Tarlinton, R. (2024). UK flockdown: A survey of small-scale poultry keepers and their understanding of governmental guidance on highly pathogenic avian influenza (HPAI). Preventive Veterinary Medicine, 224, 106117. https://doi.org/10.1016/j.prevetmed.2024.106117
  • Mendola, M. (2007). Agricultural technology adoption and poverty reduction: A propensity-score matching analysis for rural Bangladesh. Food Policy. 32(3), 372–393. https://doi.org/10.1016/j.foodpol.2006.07.003
  • OECD/FAO. (2023). OECD-FAO agricultural outlook 2023–2032. OECD Publishing. https://doi.org/10.1787/08801ab7-en
  • Robertson, T. S., & Gatignon, H. (1986). Competitive effects on technology diffusion. Journal of Marketing, 50(3), 1–12. https://doi.org/10.1177/002224298605000301
  • ROPPA. (2013). Ten years after the Maputo declaration on agriculture and food security: An assessment of progress in West Africa: CASE OF TOGO. European Centre for Development Policy Management. https://www.roppa- afrique.org/IMG/pdf/togo_rapport_final-kf.pdf
  • Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. https://doi.org/10.1017/CBO9780511810725.016
  • Rubin, D. B. (1974). Estimating causal effects of treatment in randomized and nonrandomized studies. Journal of Educational Psychology, 66(5), 688–701. https://doi.org/10.1037/h0037350
  • Schulz, D., & Börner, J. (2023). Innovation context and technology traits explain heterogeneity across studies ofagricultural technology adoption: A meta-analysis. Journal of Agricultural Economics, 74(2), 570–590. https://doi.org/10.1111/1477-9552.12521
  • Soviadan, M. K., Enete, A. A., Okoye, C. U., & Kubik, Z. (2023). Determinants of farmers’ participation in the agricultural sector support project for the adoption of improved technology in traditional poultry farming: Evidence from rural Togo. Journal of Agriculture and Environment for International Development (JAEID), 116(2), 87–108. https://doi.org/10.36253/jaeid-12642
  • Soviadan, M. K., Kubik, Z., Enete, A. A., & Okoye, C. U. (2022). Assessing the adoption rates of improved technology in traditional poultry farming: Evidence from rural Togo. African Journal of Agricultural and Resource Economics, 17(3), 206–223. https://doi.org/10.53936/afjare.2022.17(3).14
  • Tambo, J. A., & Mockshell, J. (2018). Differential impacts of conservation agriculture technology options on household income in Sub-Saharan Africa. Ecological Economics, 151(April), 95–105. https://doi.org/10.1016/j.ecolecon.2018.05.005
  • Wong, J. T., de Bruyn, J., Bagnol, B., Grieve, H., Li, M., Pym, R., & Alders, R. G. (2017). Small-scale poultry and food security in resource-poor settings: A review. Global Food Security, 15(April), 43–52. https://doi.org/10.1016/j.gfs.2017.04.003
  • Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT Press.
  • World-Bank. (2017). International Development Association (Project paper. Report No: PAD2219). https://documents1.worldbank.org/curated/en/598011492394445446/pdf/TOGO-PP-03282017.pdf
  • Yadav, G. S., Debnath, C., Datta, M., Ngachan, S. V., Yadav, J. S., & Babu, S. (2013). Comparative evaluation of traditional and improved farming practices in Tripura. Indian Journal of Agricultural Sciences, 83(3), 310–314.